A novel glycosyltransferase-related lncRNA signature correlates with lung adenocarcinoma prognosis - Bian, Chengyu; Sun, Xinti; Huang, Jingjing; Zhang, Wenhao; Mu, Guang; Wei, Ke; Chen, Liang; Xia, Yang; Wang, Jun (Frontiers in Oncology, 2022)
Background Lung adenocarcinoma (LUAD) is one of the most fatal cancers in the world. Previous studies have shown the increase in glycosylation level, and abnormal expressions of related enzymes are closely related to various cancers. Long non-coding RNAs (lncRNAs) play an important role in the proliferation, metabolism, and migration of cancer cells, but the underlying role of glycosyltransferase (GT)-related lncRNAs in LUAD remains to be elucidated. Methods We abstracted 14,056 lncRNAs from The Cancer Genome Atlas (TCGA) dataset and 257 GT-related genes from the Gene Set Enrichment Analysis (GSEA) database. Univariate, LASSO-penalized, and multivariate Cox regression analyses were conducted to construct a GT-related lncRNA prognosis model. Results A total of 2,726 GT-related lncRNAs were identified through Pearson’s correlation analysis, and eight of them were utilized to construct a GT-related lncRNA model. The overall survival (OS) of the low-risk group continued to be superior to that of the high-risk group according to the subgroups classified by clinical features. The risk model was proved to have independent prognostic characteristics for LUAD by univariate and multivariate Cox regression analyses. The status of the tumor immune microenvironment and the relevant immunotherapy response was significantly different between the two risk groups. The candidate drugs aimed at LUAD subtype differentiation were identified. Conclusion We constructed a risk model comprising eight GT-related lncRNAs which was identified as an independent predictor of prognoses to predict patient survival and guide-related treatments for patients with LUAD.